In the homepage table of lessons, we link only to the Python lessons. But now that we are starting to really ramp up with R via @R-icntay and others, we should showcase those too! We are linking to them in the lessons themselves but let's consider adding a column in the home page for R, and add the author credit to the 'author' column.

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

What happened:

If a negative value for drop_axis is passed into either map_blocks or map_overlap a non-informative exception is raised.

What you expected to happen:

I would expect this would work as in NumPy for negative axis arguments where axis becomes axis = axis % array.ndim. If it is not intended to work, then it should raise a user-friendly AxisError. This came up

Bug/Feature Request Description

In [1]: import featuretools as ft                                                                                                                             

In [2]: es = ft.demo.load_mock_customer(return_entityset=True)                                                                                                

In [3]: import pandas as pd    

Building the doc fails for example 40_advanced/example_single_configurations on the current development branch

Logs here

...
generating gallery for examples/40_advanced... [ 50%] example_debug_logging.py

Warning, treated as error:
/home/runner/work/auto-sklearn/auto-sklearn/examples/40_advanced/example_single_configu

Describe the bug
If you load arrow_head data with default split settings, the resulting dataframe has indices that repeat. this is because there is a concatenation of train and test data

To Reproduce

from sktime.datasets import load_arrow_head
X, y = load_arrow_head(return_X_y=True)
X.index.values

Output:

array([  0,   1,   2,   3,   4,   5,   6,   7,   8,

Hi! I was a bit surprised by the name of CVSplit. The name suggests that it is responsible for cross-validation, but the documentation reveals that it only trains and validates on one split. That doesn't match my understanding of cross-validation. It could [technically](https://en.m.wikipedia.org/wiki/Cross-va

Yes

When running TabularPredictor.fit(), I encounter a BrokenPipeError for some reason.
What is causing this?
Could it be due to OOM error?

Fitting model: XGBoost ...
-34.1179 = Validation root_mean_squared_error score
10.58s = Training runtime
0.03s = Validation runtime
Fitting model: NeuralNetMXNet ...
-34.2849 = Validation root_mean_squared_error score
43.63s =

Can we have an example of REST API calls in the documentation?
Examples with CURL, HTTPie or another client and the results would be better for newbies.
Thanks again for your good work.

What's wrong?